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Search Dimensionality-Reduction , found 4 results

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Scanpy Single-Cell Workflow

K-Dense-AI/claude-scientific-skills

Scanpy is a scalable Python toolkit for single-cell RNA-seq analyses, covering QC, normalization, dimensionality reduction, clustering, marker discovery, annotation, and publication-ready visualization across h5ad/10X/CSV datasets.

Fast UMAP Dimensionality Reduction

K-Dense-AI/claude-scientific-skills

Use UMAP for fast nonlinear manifold reduction to produce embeddings that keep local and global structure, making it ideal for visualization, clustering preprocessing, supervised/parametric workflows, or high-dimensional feature engineering.

Scanpy Single-Cell Workflow

K-Dense-AI/scientific-agent-skills

Scanpy is a scalable Python toolkit for single-cell RNA-seq analyses, covering QC, normalization, dimensionality reduction, clustering, marker discovery, annotation, and publication-ready visualization across h5ad/10X/CSV datasets.

Fast UMAP Dimensionality Reduction

K-Dense-AI/scientific-agent-skills

Use UMAP for fast nonlinear manifold reduction to produce embeddings that keep local and global structure, making it ideal for visualization, clustering preprocessing, supervised/parametric workflows, or high-dimensional feature engineering.

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